code: def test_append_with_other_datapipes():
      num_ids = 100
      batch_size = 4
      item_set = gb.ItemSet(torch.arange(0, num_ids))
      data_pipe = gb.ItemSampler(item_set, batch_size)
      # torchdata.datapipes.iter.Enumerator
      data_pipe = data_pipe.enumerate()
      for i, (idx, data) in enumerate(data_pipe):
          assert i == idx
          assert len(data) == batch_size
  
imports: import os
  import re
  from sys import platform
  import dgl
  import pytest
  import torch
  import torch.distributed
  import torch.multiprocessing
  from dgl import graphbolt
  from torch.testing import assert_close
label_desc: Use image node_id 10 for calling a global function with example usage: test_append_with_other_datapipes() without return types